Digital images exist in many file types (e.g., tiff, jpeg, gif, cgm, pdf), formats (e.g. raster, vector), and can be from any source and of any subject, including, but not limited to: seismic lines, photographs (aerial and other), geologic cross-sections, and well logs. Digital images are typically used out of context and apart from computer implemented interpretation applications that use information related to the digital images. For example, geoscientists may have digital images of seismic data but cannot view and interpret the images in context with other data in geologic interpretation applications. The ability to convert digital images to georeferenced multi-dimensional data structures that could be used within interpretation applications would increase the value of the digital image data.
Known methods of geo-referencing, converting and transmitting digital images to interpretation applications have generally been limited to two dimensional, black and white images, and been found to be unsatisfactory. Map-view digital images can be geo-referenced using GIS and remote sensing applications, but the resulting data format is not generally compatible with other computer applications. Moving digital images into interpretation applications involves scanning the image into a GIS application, manually digitizing each pixel as vectors, and exporting the vector data through another application. The process is labor-intensive and provides only vectorized shapes, lacking the detail of the original digital image. Other methods are limited to SEG-Y output formats, require expert computer application skills, and are: expensive, time consuming, not suitable for large-scale use, and tend to result in a loss of data quality.
Although some methods have been considered, there is a need for a method that geo-references a digital image, converts the digital image color information to a useful third dimension (for example, amplitude or depth/time) and transfers the digital image and information to an interpretation application where the image can be viewed and manipulated in context with other data.